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3D-Beacons: decreasing the gap between protein sequences and structures through a federated network of protein structure data resources
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 4660376
Author(s) Varadi, Mihaly; Nair, Sreenath; Sillitoe, Ian; Tauriello, Gerardo; Anyango, Stephen; Bienert, Stefan; Borges, Clemente; Deshpande, Mandar; Green, Tim; Hassabis, Demis; Hatos, Andras; Hegedus, Tamas; Hekkelman, Maarten L.; Joosten, Robbie; Jumper, John; Laydon, Agata; Molodenskiy, Dmitry; Piovesan, Damiano; Salladini, Edoardo; Salzberg, Steven L.; Sommer, Markus J.; Steinegger, Martin; Suhajda, Erzsebet; Svergun, Dmitri; Tenorio-Ku, Luiggi; Tosatto, Silvio; Tunyasuvunakool, Kathryn; Waterhouse, Andrew Mark; Schwede, Torsten; Orengo, Christine; Velankar, Sameer
Author(s) at UniBasel Schwede, Torsten
Tauriello, Gerardo
Bienert, Stefan
Waterhouse, Andrew
Year 2022
Title 3D-Beacons: decreasing the gap between protein sequences and structures through a federated network of protein structure data resources
Journal GigaScience
Volume 11
Pages / Article-Number giac118
Keywords bioinformatics; experimentally determined structures computationally predicted structures; federated data network; structural biology
Mesh terms Amino Acid Sequence; Databases, Protein; Computer Simulation; Metadata; Records
Abstract While scientists can often infer the biological function of proteins from their 3-dimensional quaternary structures, the gap between the number of known protein sequences and their experimentally determined structures keeps increasing. A potential solution to this problem is presented by ever more sophisticated computational protein modeling approaches. While often powerful on their own, most methods have strengths and weaknesses. Therefore, it benefits researchers to examine models from various model providers and perform comparative analysis to identify what models can best address their specific use cases. To make data from a large array of model providers more easily accessible to the broader scientific community, we established 3D-Beacons, a collaborative initiative to create a federated network with unified data access mechanisms. The 3D-Beacons Network allows researchers to collate coordinate files and metadata for experimentally determined and theoretical protein models from state-of-the-art and specialist model providers and also from the Protein Data Bank.
ISSN/ISBN 2047-217X
edoc-URL https://edoc.unibas.ch/93047/
Full Text on edoc Available
Digital Object Identifier DOI 10.1093/gigascience/giac118
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/36448847
ISI-Number MEDLINE:36448847
Document type (ISI) Journal Article
 
   

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